The Future of Data : Making connections so your users don’t have to. Presented Feb 2013 at Hack+Startup.

1. The Future of Data
In 10 minutes

2. Google 2000
Google Inc Today announced it has
released the largest search engine on the
Internet. Google’s new index, comprising
more than 1 billion URLs

3. Google 2008
Our indexing system for processing links
indicates that we now count 1 trillion unique
URLs (and the number of individual web
pages out there is growing by several billion
pages per day).

4. Data Growth
1,000
1000
750
500
500
250
250
120
55
4 10 24
1
0
2000 2001 2002 2003 2004 2005 2006 2007 2008

5. What are we doing with all this
data?

6. A brief history of data
incomplete and mostly inaccurate

7. Relational databases
became a crutch

8. Memcache, a scooter

9. Limited by our tools…

10. Shiny Raw Data

11. Around 2007
The crutches began to snap
– Social graph emergence
– Substantial data growth
– Flexible & rich data structures needed
– Open source tools emerged
– No longer just Google & Amazon

12. MongoDB, Hadoop, etc.
An empowering exoskeleton

13. Products built with these
new data tools largely
resembled earlier products

14. The crutch was gone but we
acted like it was still there

16. The data tools today are
vastly more powerful
Tools built to make
sense of our data

17. Your data is telling you things
Are you listening?

18. We need to do more than report
We need products that…
inform
educate
reveal

21. Google analytics
What if it provided actual intelligence, like…
Steve,
Your website currently has higher than usual traffic.
Most of the visitors are coming from a blog post on
Lifehacker which links to your Vim page. There's quite a
conversation happening there so you may want to
participate. Additionally the conversation seems to have
spilled over onto Twitter.

22. Google analytics
Of the people that go to MongoDB.org:
4% visited DataStax
20% visited Amazon Web Services
10% searched for cloud hosting
…

23. It's about making connections
… so your users don’t have to

24. City of Chicago

25. Goals
• Bring all the data all in one place
• Make it available in realtime
• Find relationships in the data

28. Modern tools like
Redis
Hadoop
MongoDB
Storm / Spark
R / Ruby / Python / Go
empower you

29. What are you going to do with
your data?

30. Questions
@spf13
spf13.com
MongoDB.org